Influence of Hashimoto thyroiditis on diagnosis and treatment of thyroid nodules

Elevated thyroid-stimulating hormone levels, independent of Hashimoto's thyroiditis, increase thyroid cancer risk: Insights from genetic and clinical evidence

PURPOSE

Hashimoto's thyroiditis (HT) is a prevalent autoimmune disorder and thyroid cancer (TC) is the most prevalent endocrine malignancy. Recent debates have focused on whether HT increases the risk of developing TC. This study combined Mendelian randomization (MR) and observational methods to investigate the potential causal relationship between HT and TC risk.

METHODS

First, we performed two-sample MR and multivariable MR (MVMR) analysis using the genome-wide association studies (GWAS) data from multiple databases, including European and East Asian populations, to estimate the effect of HT and thyroid-stimulating hormone (TSH) levels on TC risk. Second, we conducted an observational study using data from the National Health and Nutrition Examination Survey (NHANES) database and evaluated the association between HT, TSH, and TC prevalence through logistic regression model and restricted cubic spline model.

RESULTS

Our MR findings revealed no significant association between HT and TC risk in both populations. However, elevated TSH levels significantly increased TC and papillary thyroid carcinoma (PTC) risk, while lower TSH levels were associated with reduced TC risk. Further MVMR analysis and an observational study confirmed this. Additionally, our observational study also indicated no significant relationship between HT and TC prevalence and abnormal TSH levels correlated with higher TC risk.

CONCLUSION

HT was not a TC risk factor, but high TSH levels increased TC risk. Controlling TSH within normal ranges through thyroid hormone replacement was recommended to reduce TC risk in HT patients with elevated TSH levels, even those without symptoms.

Identification of BTK as an immune-related biomarker for Hashimoto's thyroiditis by integrated bioinformatic analysis

BACKGROUND

Hashimoto's thyroiditis (HT) is one of the most common autoimmune disorders characterized by diffuse enlargement of the thyroid gland, lymphocyte infiltration, and thyroid-specific autoantibodies. Cellular and humoral immune disorders have been implicated in the development of HT. However, little is known regarding the role of immune-related molecules in HT. This study was aimed to identify key immune-related biomarkers in HT by using bioinformatic analysis.

METHOD

Integration of the sequencing data from HT and normal control (NC) in the GSA and GTEx databases yielded a dataset named NGS. The GSE138198 dataset from the GEO database was downloaded as a validation set. WGCNA analysis was performed to identify key modules associated with HT. Lasso regression analysis (LASSO) and random forest (RF) were performed to determine potential diagnostic biomarkers. The potential value was assessed by using receiver operating characteristic (ROC) curve analysis. CIBERSORT algorithm was used to evaluate the infiltration of immune cells in HT and NC samples. The transcript levels of verified genes from expanded samples were detected by quantitative real-time PCR.

RESULTS

A total of 1,401 differentially expressed genes (DEGs) were identified in HT patients. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses indicated that these DEGs were predominantly enriched in immune-related pathways. Furthermore, 192 immune-related genes were identified in HT through the intersection of WGCNA modules, DEGs, and the IRGs. Among them, two upregulated genes ((Bruton's tyrosine kinase, BTK) and CD19) showed the potential diagnostic value for HT by using machine learning. The ROC curve analysis revealed that BTK had a higher diagnostic value than CD19 across two datasets. Intriguingly, only BTK expression was upregulated in the peripheral blood mononuclear cells of HT patients, and was significantly positively correlated with the serum levels of thyroid autoantibodies. Further studies confirmed a significant positive correlation between BTK and increased proportions of plasma cells in HT patients.

CONCLUSION

This study identified BTK was significantly increased in HT patients, which might be the involved in the pathogenesis of HT by regulating plasma cells and represented a potential immune-related biomarker of HT.

Analysis of BRAF Gene Mutation in Hashimoto's Thyroiditis With Multifocal Papillary Thyroid Carcinoma

BACKGROUND

Thyroid cancer (TC) is a highly prevalent malignant tumor of the head and neck. Papillary thyroid carcinoma (PTC) is the primary pathological type of TC, accounting for more than 80% of all TCs. BRAF mutations are closely associated with PTC. However, the relationship among HT, PTC, and BRAF mutations has not yet been clarified. We aimed to investigate the BRAF mutation in Hashimoto's thyroiditis (HT) with PTC.

METHODS

A total of 72 patients with multifocal PTC were included and grouped based on surgical pathology examination. Group A (n = 32) had pure multifocal PTC and Group B (n = 40) had HT with multifocal PTC. Various features were compared: BRAF mutation, multifactorial analysis of BRAF mutations, pathological features in patients with HT and multifocal PTC, and multifactorial analysis of factors affecting HT with multifocal PTC.

RESULTS

Significant differences were seen in thyroid peroxidase antibody levels, central lymph node metastasis, extra-thyroidal invasion, main and non-main lesion diameters, and BRAF mutation positivity (P < 0.05). Patients with the BRAF mutation had significantly higher rates of extra-thyroidal invasion and lymph node metastasis than those without the BRAF mutation (P < 0.05). Logistic regression analysis showed that BRAF mutation and main lesion nodule diameter were independent risk factors affecting extra-thyroidal invasion and central lymph node metastasis in patients with HT and multifocal PTC (P < 0.05).

DISCUSSION

BRAF mutations were more prevalent and closely associated with extra-thyroidal invasion and central lymph node metastasis in patients with HT and multifocal PTC.

Detection of malignant lesions in cytologically indeterminate thyroid nodules using a dual-layer spectral detector CT-clinical nomogram

Purpose

To evaluate the capability of dual-layer detector spectral CT (DLCT) quantitative parameters in conjunction with clinical variables to detect malignant lesions in cytologically indeterminate thyroid nodules (TNs).

Materials and methods

Data from 107 patients with cytologically indeterminate TNs who underwent DLCT scans were retrospectively reviewed and randomly divided into training and validation sets (7:3 ratio). DLCT quantitative parameters (iodine concentration (IC), NICP (IC nodule/IC thyroid parenchyma), NICA (IC nodule/IC ipsilateral carotid artery), attenuation on the slope of spectral HU curve and effective atomic number), along with clinical variables, were compared between benign and malignant cohorts through univariate analysis. Multivariable logistic regression analysis was employed to identify independent predictors which were used to construct the clinical model, DLCT model, and combined model. A nomogram was formulated based on optimal performing model, and its performance was assessed using receiver operating characteristic curve, calibration curve, and decision curve analysis. The nomogram was subsequently tested in the validation set.

Results

Independent predictors associated with malignant TNs with indeterminate cytology included NICP in the arterial phase, Hashimoto's Thyroiditis (HT), and BRAF V600E (all p < 0.05). The DLCT-clinical nomogram, incorporating the aforementioned variables, exhibited superior performance than the clinical model or DLCT model in both training set (AUC: 0.875 vs 0.792 vs 0.824) and validation set (AUC: 0.874 vs 0.792 vs 0.779). The DLCT-clinical nomogram demonstrated satisfactory calibration and clinical utility in both training set and validation set.

Conclusion

The DLCT-clinical nomogram emerges as an effective tool to detect malignant lesions in cytologically indeterminate TNs.

Does vitreous haemorrhage and calcification lead to increased risk of enucleation in advanced retinoblastoma?

PURPOSE

To explore whether varying degrees of vitreous haemorrhage (VH) and calcification act as risk factors for enucleation in patients with advanced retinoblastoma (RB).

METHODS

Advanced RB was defined by the international classification of RB (Philadelphia version). Basic information for retinoblastoma patients diagnosed as groups D and E in our hospital between January 2017 and June 2022 was reviewed by logistics regression models. Additionally, a correlation analysis was performed, excluding variables with a VIF (variance inflation factor) >10 from the multivariate analysis.

RESULTS

A total of 223 eyes diagnosed with RB were included in assessing VH and calcification; of these, 101 (45.3%) eyes experienced VH, and 182 (76.2%) eyes were found to have calcification within the tumour through computed tomography (CT) or B-scan ultrasonography. Ninety-two eyes (41.3%) were enucleated, of which 67 (72.8%) had VH and 68 (73.9%) calcification, both of which were significantly relevant to enucleation (p < 0.001*). Other clinical risk factors, such as corneal edema, anterior chamber haemorrhage, high intraocular pressure during treatment and iris neovascularization, correlated significantly with enucleation (p < 0.001*). Multivariate analysis included IIRC (intraocular international retinoblastoma classification), VH, calcification and high intraocular pressure during treatment as independent risk factors for enucleation.

CONCLUSIONS

Despite identifying different potential risk factors for RB, there remains significant controversy concerning which patients require enucleation, and the degree of VH varies. Such eyes need to be evaluated carefully, and management with appropriate adjuvant therapy may improve the outcome of these patients.

Prognosis and influencing factors of follicular thyroid cancer

OBJECTIVES

Follicular thyroid cancer (FTC) is prone to distant metastasis, and patients with distant metastasis often have poor prognosis. In this study, the impact of metastasis and other relevant factors on the prognosis of follicular thyroid carcinoma was examined.

METHODS

This was a retrospective study. Data were obtained from Zhejiang Cancer Hospital, Sun Yat-sen University Cancer Center and Hangzhou First People's Hospital affiliated with Zhejiang University School of Medicine, from January 2009 to June 2021 for 153 FTC patients. The patients were assigned into three groups according to their distant metastasis: distant metastasis at initial diagnosis (M1), distant metastasis during follow-up (M2), and no evidence of distant metastasis over the course of the study (M0). Data were collected and summarized on clinical data, laboratory parameters, imaging features, postoperative pathologic subtypes, and metastases. The Cox proportional hazard model was used to perform the univariate and multivariate analysis. Kaplan-Meier curves were used to evaluate cancer-specific survival (CSS).

RESULTS

Based on metastasis, the patients were assigned into three groups, including 31 in the M1 group, 15 in the M2 group, and 107 in the M0 group. These individuals were followed up for an average of 5.9 years, and the group included 46 patients with distant metastasis (31 confirmed at diagnosis and 15 found during follow-up). Univariate Cox regression analysis showed that age, Hashimoto's thyroiditis (HT), surgery method, postoperative adjuvant therapy, histologic subtype, nodule size, calcification, TSH, and distant metastasis all impacted prognosis. Multivariate Cox regression analysis suggested that histologic subtype (widely invasive; HR: 7.440; 95% CI: 3.083, 17.954; p < 0.001), nodule size (≥40 mm; HR: 8.622; 95% CI: 3.181, 23.369; p < 0.001) and distant metastasis (positive; HR: 6.727; 95% CI: 2.488, 18.186; p < 0.001) were independent risk factors affecting the prognosis of follicular thyroid cancer.

CONCLUSIONS

Histologic subtype, nodule size, and distant metastasis are important risk factors for the prognosis of follicular thyroid cancer. Patients with metastatic follicular thyroid cancer have a poor prognosis, especially with metastasis at the time of initial diagnosis. As a result, this group of patients requires individualized treatment and closer follow-up.

Radiomics-based ultrasound models for thyroid nodule differentiation in Hashimoto's thyroiditis

Background

Previous models for differentiating benign and malignant thyroid nodules(TN) have predominantly focused on the characteristics of the nodules themselves, without considering the specific features of the thyroid gland(TG) in patients with Hashimoto's thyroiditis(HT). In this study, we analyzed the clinical and ultrasound radiomics(USR) features of TN in patients with HT and constructed a model for differentiating benign and malignant nodules specifically in this population.

Methods

We retrospectively collected clinical and ultrasound data from 227 patients with TN and concomitant HT(161 for training, 66 for testing). Two experienced sonographers delineated the TG and TN regions, and USR features were extracted using Python. Lasso regression and logistic analysis were employed to select relevant USR features and clinical data to construct the model for differentiating benign and malignant TN. The performance of the model was evaluated using area under the curve(AUC), calibration curves, and decision curve analysis(DCA).

Results

A total of 1,162 USR features were extracted from TN and the TG in the 227 patients with HT. Lasso regression identified 14 features, which were used to construct the TN score, TG score, and TN+TG score. Univariate analysis identified six clinical predictors: TI-RADS, echoic type, aspect ratio, boundary, calcification, and thyroid function. Multivariable analysis revealed that incorporating USR scores improved the performance of the model for differentiating benign and malignant TN in patients with HT. Specifically, the TN+TG score resulted in the highest increase in AUC(from 0.83 to 0.94) in the clinical prediction model. Calibration curves and DCA demonstrated higher accuracy and net benefit for the TN+TG+clinical model.

Conclusion

USR features of both the TG and TN can be utilized for differentiating benign and malignant TN in patients with HT. These findings highlight the importance of considering the entire TG in the evaluation of TN in HT patients, providing valuable insights for clinical decision-making in this population.

Risk factors and predictive model for recurrence in papillary thyroid carcinoma: a single-center retrospective cohort study based on 955 cases

Background

The 2015 American Thyroid Association guidelines proposed recurrence risk stratification of differentiated thyroid carcinoma, including papillary thyroid carcinoma (PTC), but this stratification excluded non-initial treatment patients with worse outcomes. This study aimed to explore the potential risk factors for recurrence in PTC and develop a predictive model for both initial and non-initial treatment of patients with PTC.

Methods

A total of 955 patients were included in this study. Differences between the recurrence (-) and recurrence (+) groups were compared. The 955 patients were randomized into two groups: the training group (671 cases) and the validation group (284 cases). All variables were selected using the LASSO regression analysis. A nomogram was developed based on the results of the univariate and multivariate logistic regression analyses. The nomogram performance was evaluated using discrimination and calibration.

Results

Patients aged ≥55 years, extranodal extension (ENE), metastatic LN ratio (LNR) >0.5, and non-initial treatment were identified as potential risk factors for recurrence through LASSO regression and univariate and multivariate analyses. The receiver operating characteristic curve (ROC curve) showed high efficiency, with an area under the ROC curve (AUC) of 0.819 (95% confidence interval [CI], 0.729-0.909) and 0.818 (95% CI, 0.670-0.909) in the training and validation groups, respectively. The calibration curve indicated that the nomogram had a good consistency.

Conclusion

In patients with PTC, age ≥55 years, ENE, LNR >0.5, and non-initial treatment are potential risk factors for recurrence. The predictive model of recurrence was confirmed to be a practical and convenient tool for clinicians to accurately predict PTC recurrence.

Geographic variation in the association between Hashimoto's thyroiditis and Papillary thyroid carcinoma, a meta-analysis

PURPOSE

The association between papillary thyroid cancer (PTC) and Hashimoto's thyroiditis (HT) remains a matter of debate. Several genetic and environmental factors have been found to influence this association. Because of the variation in these factors among different populations, we conducted a country- and region-based meta-analysis to examine whether the geographic area influences this association.

METHODS

We searched PubMed and Web of Science databases for original articles that investigated the association between HT and PTC from February 1955 to February 28, 2023. The included studies were stratified according to their country and region of origin. Various subgroup analyses were conducted. The primary outcome was the pooled relative risk (RR) and its 95% confidence interval (CI) for each region and country.

RESULTS

Forty-six studies including a total of 93,970 participants met our inclusion criteria. They originated from 16 countries distributed in five regions. Significant variation was found among countries but not among regions. Upon analysis of all 46 included studies, countries were classified based on their RR and its 95% CI. Excluding countries with pooled sample sizes <500, Sri Lanka (RR 4.23, 95% CI 2.91-6.14), Poland (RR 3.16, 95% CI 2.79-3.57) and Japan (2.68, 2.14-3.36) showed the strongest association between HT and PTC while Greece (RR 1.06, 95% CI 1.00-1.13), Spain (RR 0.70, 95% CI 0.23-2.11), and Jordan (0.62, 0.32-1.32) showed no significant association.

CONCLUSION

Our findings revealed a variation in the association between HT and PTC among countries but not among regions. The country-to-country variation could be due to certain genetic and/or environmental factors subject to geographic variation that influence this association. These findings may help guide health policies aiming to mitigate the risk of PTC in the HT population by helping identify high-risk and low-risk countries.

Identification of SERPINA1 promoting better prognosis in papillary thyroid carcinoma along with Hashimoto's thyroiditis through WGCNA analysis

Background

Hashimoto's thyroiditis (HT) is an autoimmune thyroid disease. Papillary thyroid carcinoma (PTC) is the most common endocrine cancer. In recent years the rate of coexistence between PTC and HT has increased but the relationship between them remains unclear, meaning it is necessary to find potential biomarkers for PTC coexistence with HT to predict its potential pathways.

Method

A co-expression network was constructed using the weighted gene co-expression network analysis (WGCNA) in the R package. The modules of PTC associated with HT (PTC-W) were identified from the GSE138198 dataset. Protein-protein interaction network (PPI) was used to screen the hub genes. Immunohistochemical (IHC) analysis was performed to validate the expression of the hub genes in tissues. Clinical data from The Cancer Genome Atlas (TCGA) datasets were used to analyse the prognosis of the hub genes. Gene set enrichment analysis (GSEA) was used to screen potential pathways of PTC-W.

Result

The MEbrown module representing the most significant module, with 958 differentially expressed genes (DEGs), was screened in PTC-W, based on WGCNA analysis. Through PPI, SERPINA1 was identified as a hub gene. Immunostaining validated that SERPINA1 was highly expressed in PTC-W. Moreover, PTC-W expressing SERPINA1 exhibits a better prognosis than PTC without HT (PTC-WO).

Conclusion

Our study demonstrates that SERPINA1 promotes the occurrence of PTC-W, and its prognosis is better than PTC-WO. SERPINA1 promotes a better prognosis for PTC-W, possibly through a tumour inhibition signalling pathway.